Artificial Intelligence in Health Care: A New opportunity to build Career

In lockdown era of Covid-19 outbreak, creates a recession in different working sectors and numerous people lost their jobs in different areas.  After pandemic, new job opportunities have been opened up. Among them, AI in health care is considered as one of the promising one. In the context of covid-19 pandemic there exist shortage of health care personnel and this not fulfilling the diagnosis response at the emergency stage. Integration of AI in health care can be considered as a promising option to overcome the shortage of health care personnel. Now question is that how a computer Engineer can incorporate AI in health care. The applications of AI into health care have been categorized into three groups.

  • Patient-oriented AI
  • Clinical oriented AI
  • Administration and operational Oriented AI

The Patient oriented AI system can directly improve the patient care. According to the report of UK Govt., if the AI-enabled symptoms checker is coupled with the telemedicine technology, reduced number of physicians visits in hospitals. Different Machine Learning and deep learning-based (ML/DL) algorithms have been considered to train the aforementioned AI-enabled symptoms checker system where the several symptoms of the common diseases have been considered as the training data.

 Apart from this, several organizations adopted the chatbot system to improve the patient care. Chatbot is a software program that automatically chat with the patients through text or voice messages. A chatbot system, initially collects information from patients. After analyzing this information using different Computer vision techniques, provides the information regarding the present conditions of the disease as well as, what he will do. In some places, the chatbot systems are not capable of collecting the patients’ information, a wearable device can play an important role. These wearable devices sense the patient’s disease information through some sensors and AI-based methodologies provide the actual conditions of the disease. Another noteworthy fact is that AI can improve the accuracy in disease detection.

 In developing countries like India, the doctor and patient are low and an individual clinician works nearly 14-18 hours in a day. Due to this extensive workload, clinicians may overlook the early sign of the disease. A computer aided diagnosis system (CAD) can assist doctors to detect these symptoms at the early stages. The researchers from University of Calcutta said that their implemented CAD system is capable of detecting lung nodules at early stages which may indicate lung cancer if it is detected at later stages.

Furthermore, AI can also increase the efficacy of the targeted therapy. AI is capable of identifying the accurate effected area of the abnormal tissue. By supervising the effected area through computers, a clinician can provide the drug to the patients.

Apart from the computer vision techniques, the natural language processing (NLP) also improves the clinical outcomes. In daily clinical practice, clinicians often required previous disease history, medications doses and the family history of the disease to prepare appropriate diagnose plan. In health sector, the data are stored in an unstructured manner i.e., the health sector-maintained paper-based work. Due to extensive workload these data may lost. The Electronic Medical Record or EMR is a software where the NLP techniques can store large number of clinical text data in a structured form. In present context, the existing EMR software is very costly. This necessitates the AI-based health care industry to implement a low cost and more accurate EMR tool for improved diagnosis procedures. The Norway based Globus.ai’s AI enabled EMR system shows that it fills clinical data 90% more faster than the human work. Another interesting application of AI in health care is robotic surgery. In this application, different computer algorithms have been automated for different surgeries. However, the general decisions are still taken by the surgeon.  

Beside the clinical outcomes, AI can also improve the patient safety. It has been observed that, several patients suffer from adverse drug effects i.e., the drug is not suited for the patient body. Israel’s MedAware’s patient safety platform considered different ML algorithms to detect and reduce the risk of medication error.

This discussion reveals that to provide improved health care, participation of AI engineers in heal care industry become an inevitable option. This creates huge job opportunities to the engineers.

Career as a Machine Learning Engineer in the post-pandemic world

The entire globe has been facing an unprecedented challenge from the Novel Coronavirus, which has made the physical world come to a standstill and the world economy has been holding onto a thread due to this fatal pandemic. But the brighter side of this gloomy situation is that companies are finally appreciating and understanding the significance of Machine Learning and Artificial Intelligence in the practical world. More and more brands are now taking up Machine Learning solutions for their business problems. Not only Machine Learning is used to combat the global pandemic but it has also come out as an important tool in constructing a better world post-COVID. Machine Learning has the capability of providing an understanding and early analysis of problems and prompt resolutions. This technology is used by the doctors and health practitioners to track the virus, identify potential threat to patients and predict the possible cure from disease. These reasons indicate that Machine Learning and Artificial Intelligence, both are here to rule and this can be an interesting career option for the aspirants who are passionate about data and numbers. Machine Learning has been at the forefront for all the advanced programmers who intend to develop intelligent systems that learn and apply knowledge. These programmers, better known as Machine Learning (ML) engineers, train systems with the help of complex datasets and algorithms.

Machine learning brief explanation

Machine Learning is a subset of Artificial Intelligence, which combines Statistics and Computer Science to predict using different mathematical models. The predictive model can be based on like whether an image contains cat or dog, predicting credit card fraud detection etc. The main objective of Machine Learning is to take decisions based on predictive modelling. Hidden patterns across the datasets are extracted and useful insights about data are found out to drive important decisions, improve customer relationship based on feedback patterns or launch new business.

What are the pre-requisites for becoming a Machine Learning engineer?

A Machine Learning engineer requires to be proficient in a bunch of technical skills for building predictive models.

Below are given some of the primary components of the Machine Learning engineer role:

  • Data: The Machine Learning engineer has to understand the importance of data in predictive modelling. The data pre-processing is one of the important steps for constructing a Machine Learning model. Data has to be analysed and described in terms of the problem requirement. Good quality data is a necessary requirement in building efficient Machine Learning model.
  • Predictive Models: Machine Learning engineers need to construct the models designed by the data scientists, understand the model validation in order to get an essence of the estimation of value addition to the business and understand how to fine-tune these models to optimize them for the consumption by end users.
  • Software Engineering: They need to be efficient in coding back-end so that the models can be made available to users through a user-friendly API.
  • Efficient Scaling of Infrastructure: They need to keep the system prepared for scaling of infrastructure so that the system may not collapse when multiple number of users start operating their models.

Where is Machine Learning used in real life?

Machine Learning is being used in real life in many fields, industries or domains. Some of the application areas of Machine Learning are listed below:

  • Image Recognition: It is a popular and widely used application area of Machine Learning. This is used to identify an object from a digital image.

Some of the use-cases of Image Recognition:

  • Photograph-tagging in social media
  • Hand-writing recognition by segregating a single letter into component images
  • Speech Recognition: Machine Learning has the capability of translating speech into text.

Some of the use-cases of Speech Recognition:

  • Voice-based digital assistants like Amazon Alexa or Google Home etc.
  • Search based on voice
  • Dialling based on voice
  • Symptom analysis in healthcare domain: Machine Learning can help the medical practitioners to ascertain symptoms in diseases by leveraging the capability of chat bots. This is called symptom analysis which utilises the power of Natural Language Processing and text mining etc. to analyse the disease symptoms and predict the next steps to be taken as precautionary measures or remedial measures.

Primary objectives of a Machine Learning Engineer

Primary responsibilities of a Machine Learning engineer lies in creation of Machine Learning models and re-training models as and when required. Some of the common responsibilities of the role relate to:

  • Machine Learning system design
  • Implementation of Machine Learning algorithms and tools
  • Dataset selection and dataset representation methods
  • Verification of data quality
  • Accomplishing statistical analysis
  • Executing Machine Learning tests
  • Improving Machine Learning models by tuning of models by proper selection of hyper-parameters
  • Constructing Machine Learning apps as per requirement

Now, let us see the skill sets that are important for a Machine Learning Engineer.

Skill set of a Machine Learning Engineer

For becoming a Machine Learning Engineer, an aspirant should have the following skills:

  • Mathematical and statistical skills relating to subjects such as Calculus, Linear Algebra, Statistics etc.
  • Advanced degree in Computer Science, Mathematics, Statistics or a related degree
  • Master’s degree is desirable in Machine Learning, Deep Learning or related fields
  • Coding in programming languages like Python, R etc.
  • Skills pertaining to Software Engineering, Computer Architecture, Data Science and the like
  • Working experience with Machine Learning packages and libraries etc.

References:

  1. Rise in the demand for Machine Learning & AI skills in the post-COVID world, https://timesofindia.indiatimes.com/spotlight/rise-in-the-demand-for-machine-learning-ai-skills-in-the-post-covid-world/articleshow/75464397.cms
  2. Machine learning engineer (ML engineer), https://www.techtarget.com/searchenterpriseai/definition/machine-learning-engineer-ML-engineer#:~:text=Machine%20learning%20engineers%20design%20and,data%20engineers%20and%20data%20architects.
  3. AI/ML Remains The Most In-Demand Tech Skill Post COVID, https://analyticsindiamag.com/ai-ml-remains-the-most-in-demand-tech-skill-post-covid/
  4. AI, Automation and In-Demand Skills for a Post-Pandemic World, https://www.sigconsult.com/blog/2021/03/ai-automation-and-in-demand-skills-for-a-post-pandemic-world?source=google.co.in
  5. Artificial Intelligence in a post-pandemic world of work and skills, https://www.cedefop.europa.eu/en/news/artificial-intelligence-post-pandemic-world-work-and-skills

5G Implementation to 6G Evolution in IoT

The change from landline phones to the movability that 1G distant advancement offered was an immense leap. However, in our view, the leap from 4G to 5G is in much the same way enormous, as 5G is the vessel that will broaden the Internet of Things (IoT) climate decisively. We expect the creating number of related contraptions passing on at higher multi-gigabit data speeds and dare to increase network capacity to work with 5G’s gathering rate. Besides, as individual and corporate clients experience 5G’s benefits, they will clear a path for 6G’s augmentation — which history proposes is most likely going to come sooner than later.

Key Points

  • Broadband IoT, including 4G and 5G far off headways, is ready to outperform 2G besides, 3G as the part that engages the greatest piece of IoT applications from one side of the planet to the other by 2027.
  • The amount of related IoT contraptions generally extended by around 9% in 2021 to 2.3 billion unique endpoints. Moreover, that number should pass twofold to more than 27billion when 2025.
  • The energy for 5G continues to grow with associations beforehand executing the advancement. 5G should make 4G old by 2030, along these lines, with everything taken into account 6G could be Again ready to change IoT.

5G Network Expected to Widespread in 2025

As with each new alliance, a mass get-together of 5G will take time, yet not as much time as its forerunners. The 3G social affair wasn’t fast due to purchasers floundering towards change and 3G’s more extreme expense networks. The clearest system for drawing in an agreed data network development combines exploring the speed at which past cell networks were made. Shipped off in 2001, 3G cell networks didn’t change into the norm until 2007, when clients embraced 3Gconnected phones — four years after 3G opened up and 16 years after 2G moderate accessibility opened up. Generally, 4G cell networks were conveyed in 2009 and changed into the standard four years eventually later in 2013 — two years faster than the 2G to 3G change and simply a brief timeframe after 3G shipped off.

Cell Information Network Ages as The Years Progressed
Cell Information Network Ages as The Years Progressed

As per these certain examples, we expect 5G’s gathering rate to go on in the steps of 4G’s fast move to standard. After a restricted scope course of action in 2015, as attempts began testing 5G advancement, current appraisals suggest an overall inevitable gathering of 5G occurs in 2025 4G flexible enrolments are projected to top at 4.7 billion in Quarter 4 2021, and a short time later constantly decline to 3.3 billion around the completion of 2027, as 5G transforms into the fundamental participation choice.

Data Communication Lifecycle
Data Communication Lifecycle

Telecoms Report for 5G Adoption Evident Already

In its middle, 5G is planned to further develop the IoT’s buying experience. Purchasers will need to get to cloud organizations rolling from multiplayer cloud gaming, extended reality (AR)- filled shopping experiences, and permission to free robots for movements. As buyers experience 5G power, the more they’re likely going to research. Additionally, according to telecom providers, the word is getting out. Verizon itemized that 25% of its buyer distant clients used 5G-capable contraptions under a year after their conveyance, well before 4G’s 10% gathering rate a year after ship off. As a part of the 5G increment, telecoms are shutting down additional laid outages, including 3G, to reuse frequencies and work on their 4G and 5G associations. AT&T logically progressed away from the 3G relationship in February 2022 T-Mobile means to make a move as needs be in July, and Verizon before the ongoing year’s over by the completion of 2027, 40% of cell IoT affiliations should be broadband IoT (4G/5G).

5G Plan to Overtake Market
5G Plan to Overtake Market

5G’s Power on display

A couple of extraordinary IoT associations are early adopters of 5G advancement. From time to time, 5G made their more prepared models old. In various cases, 5G nudged the improvement of new advances. One model is Qualcomm’s Snapdragon, the association’s adaptable structures on a chip (SoC) thing suite. In handsets, the Snapdragon 8 Gen 1 is the world’s most significant 5G modem-radiofrequency reply for showing up at a 10-gigabit download speed or 10,000 megabits. At this speed, colossal data records can be downloaded rapidly. For setting, 4K spouting across different contraptions expects around 100 megabits or 1% of Snapdragon 8 Gen 1’s most extreme limit. Qualcomm checks that 5G-engaged handsets will show up at 750 million units sold in 2022. Cisco’s Catalyst 900X trading stage is another model. In light of Cisco’s Silicon One development, the 900X licenses the association to use quick Wi-Fi 6E sections to give 5G and cloud-based game plans. It expands the presence of existing cabling from 1 to 10 gigabits. Cisco hopes to offer 5G as an a-organization game plans commonly open to private endeavors, the advancement ability of which could be gigantic given the prerequisite for further developed data speeds, cloud accessibility, and flexibility in blend strategies. All around, attempts reliant upon security, similar to the Federal Emergency Management Agency, and organizations, such as programming as-expert association, Zendesk, relied upon Cisco’s switch advancement. Cisco expects spending on private LTE and 5G association establishment by relationship to outperform $5.7 billion by 2024. Likewise, mechanical innovation association ABB worked together with frameworks organization and telecom association Ericsson to make the keen handling plants address what might be on the horizon. ABB expects to include 5G advancement to motorize client help with utilities, present-day, transport, and structure pieces. 5G should allow more modern office robots to exploit the cloud for more unmistakable figuring power and discard comparatively inefficient and extreme in-house central dealing with units or plans taking care of units. All the while, robots can be controlled utilizing a 5G remote organization inside a distance of 1.5 kMS and in any case show steady control, given 5G’s super-low torpidity capacities. The overall market for 5G in cloud mechanical innovation should create at a 79.2% form yearly improvement rate to reach $10.6 billion by 2028.

5G Adoption to Surface the Way for 6G

We guess that fundamental tailwinds ought to result from 5G’s ability to relate, all things considered, everyone and everything speedier and more strongly than any time in late memory. Additionally, 5G’s accelerated gathering rate near to its predecessors will set up the overall economy for an altogether faster rollout representing things to come. 6G, which could hit the market by 2030, will offer more imperative use of circled radio access association (RAN), terahertz (THz) range for essentially more prominent cut off, lower dormancy, and better reach sharing so various classes of clients can safely have a comparative repeat gathering. With inventive work in progress starting around 2020, 6G will progress IoT impressively further towards a possible destiny of totally savvy and autonomous structures. Regardless, first, we’ll embrace 5G and its benefits as a general rule, which are currently starting to show up.

Advantages of 5G Communication

Fast Speed: The zenith speed of 5G correspondence can reach to 10Gbps up and 20Gbps down. Clients can truly experience speeds of 50Mbps up and 100Mbps down.

High cut off: 5G correspondence network is prepared for supporting high-thickness contraption affiliations and high breaking point data transmission. The presentation rundown of a 5G correspondence network is 1,000,000 contraption relationships for each square kilometer. Meanwhile, the display record of a 5G correspondence network is 10Mbps data transmission capacity per square meter.

High unfaltering quality: 5G correspondences support significantly strong data affiliations. Additionally, a show indication of high steadfastness tends to 0.001% package incident rate. This speed is like fiber optic trades. 5G correspondence network utilizes the consideration and convenience of low repeat band and the high information move limit and high speed of high repeat band to give high trustworthiness correspondence to clients through multi-affiliation advancement.

Low deferral: 5G correspondence has unimaginably low dormancy. Moreover, the typical show record of 5G correspondence’s beginning to end inaction is 1ms.

Low power use: 5G correspondence can figure out the traits of low power usage in unambiguous circumstances. 5G correspondence maintains high rest/development extent and broadened rest when no data is conveyed. In low power wide locale association (LPWAN), IoT has a remarkable application prospect.

6G Infrastructure Scenarios

Other than the utilization of new recurrence goes, an examination concerning new organizations is necessary. While certain uses of 5G will likewise keep on being conveyed in the current 5G groups, which, over the long run, perhaps rethought to 6G.

Industrial Networks

While 5G was inventive in presenting the chance of industry 4.0, we infer that 6G will take colossal steps in changing the social occasion and creation processes. The improvement of present-day affiliations will rely on useful social affairs of current and future radio access advances to the key business 4.0 and past use cases. Current associations are viewed as privatized, zeroing in on insane persevering through quality and ultralow idleness.

The critical strategy use cases are:

  1. Correspondence among sensors and robots
  2. Trades across different robots for coordination of attempts
  3. Correspondence between human current office heads and robots.

Right now, to accomplish the necessities for ultrahigh unwavering quality, most of the business approaches are going on a few spots in the extent of 3.4 and 3.8 GHz, where the spread divert is decently rich to the degree that diffraction ability. Regardless, machines with immense openness in the 6G period will likewise request high information rates close by advancing control and Al to have the decision to convey and manage top-quality visual information, drawing in robotized twins of machines and activities, too s remote inspecting. To this end, we expect the utilization of millimeter Wave frequencies notwithstanding bundles under 6 GHz for the present-day relationship over the going 10 years.

Wireless Personal Area Networks(WPANs)

One more area of affiliation is WPANS and far-off areas (WLANs). These WLANs’ astoundingly short affiliations may be under 0.5-1 m for WPANS and up to 30 m for WLANs. All window WLANs sight be reasonable for this application, taking into account that the affiliation money-related course of action can meet how episode when the higher windows are utilized and where genuine execution advancements exist.

Autonomous Vehicles and Smart Vehicles say Networks

6G could be utilized for data splitting between free vehicles and V2I. In any case, there are questions are expecting traffic conditions and brief distances considering showing up at deterrents talked about before will make the THz packs appropriate for this application. Further, in more, the speedy adaptable relationship between getting wires on train ate roofs and foundations can be utilized for transmission of both thriving’s fundamental data and outright pilgrim information. Such incredibly high rate joins are fitting for THz, yet the high cover ability makes serious areas of strength for beamforming bungles and expected issues with the Doppler spread. While the speed of current fast trains is fundamentally solid, and thus, shafts can be controlled in the right course settled on supposition, the required beamforming gain (and related thin bar width) makes the design touchy to even little deviations from the measures. Besides, high-rehash designs can comparatively be utilized for access among UES and radio wires in the lodges that outright the traveller information, like a (moving) area of interest. Recalling the arising 6G use cases, explicit prerequisites, new recurrent social events, and key sending conditions, we examine the developments expected to be the course of action of 6G radio and centre affiliation plans.

 

Why Computer Science?

“The Computer was born to solve the problem that did not exist before” – Bill Gates.

As a machine reduces the work effort, so does a computer for a typical complex computation. Computer science forces you to deal with a problem in a slightly different way which is a skill that can be applied to life itself. In the era of data, a computer is the most indispensable thing we can think of. Computer science gives you an opportunity in working and understanding hands-on the aspect of data.

Computer Science is the study of principles and the use of computers. The classical areas for a computer science course include discrete mathematics, data structure, theory of computation, compiler design, analysis and designing of Algorithm. The advanced study includes artificial intelligence (AI), computer networks and security, database management systems, computer vision and graphics, numerical analysis, software engineering, bioinformatics.

Apart from this, a computer engineer is supposed to be known as a fluent coder. Coding is the ‘Bread and Butter’ for all computer engineers. Programming or coding is an intriguing sector as it gives us the superpower to regulate computer programs on the go. The main goal for a computer engineer is to make a problem understandable to a machine so that it could solve the problem obligingly. The fluency and smoothness of an application are solely based on the way you design the code. C, the mother of all programming languages, is a general-purpose programming language that is extremely popular, simple, and flexible to use. It helps a programmer to build the base of designing a program.  It is a structured programming language that is machine-independent and extensively used to write various applications, Operating Systems like Windows, and many other complex programs like Oracle database, Git, Python interpreter, and more. Java, a high-level programming language, is also the most popular language for its design structure using object-oriented concepts (OOP). When it comes to the web, Java is unparallel. Most of the web-based applications are based on java. Apart from this, there are several programming languages like c++, python, Matlab, R to name a few.

There are innumerable and varied specialization and career options for a computer engineer. After completing his/her B.Tech degree a student may get absorbed in the software industry or may opt for higher studies. There are multiple sub-division and specializations in Computer Engineering which require applications in various sectors. Student can also pursue B.Tech degree in various applied fields:

  • AI/ML: Artificial Intelligence (AI) are emerging fields that will shape and dominate the future of this universe. Data is one of the most important assets of a company or government agency. It helps us to predict the future based on past experiences. AI has the potential to vastly change the way that humans interact, not only with the digital world but also with each other, through their work and other socioeconomic institutions – for better or for worse. A vast volume of data can be analysed by using a smart alternative, Machine Learning. It can produce an accurate result by designing a fast and efficient model for real-time data.
  • Blockchain: The duration of the course for B.Tech with specialization in blockchain is four years. Blockchain is currently booming and one of the most popular technologies that have invaded to almost every industry in the world. The world is changing its shape towards cryptocurrency. In near future, Bitcoin will be one of the popular transaction media. The main technology behind this is the blockchain. The technology will help the student to learn different algorithms and to curate the bitcoin on their own.
  • Cyber Security: Cybersecurity provides an expertise insight analysis on global security threats. In the world of web, to provide a secure web service is one of the main goals. The course on Cyber Security will help to learn different algorithms along with the expertization on ethical hacking, penetration testing, digital forensics. There are immense career avenues open for specialization in cybersecurity. This includes Security software developer, security analyst, security architect etc.
  • M.Tech Degree in Computer Science: Apart from doing graduation and going for an early job, a student may go for a master’s degree in computer science and engineering along with the specialized degree discussed above.

With the knowledge and concept in the domain, a computer science engineer can be eligible for an immense variety of job opportunities. Some of them are jotted below:

  1. Computer Science engineers are the primary resource of the software industry. With a sound concept in the subject, a student can crack any of the big houses easily.
  2. Government sectors such as I.S.R.O, B.H.E.L, etc are recruiting computer science engineers having a good GATE score.
  3. Interdisciplinary research is a new trend for Computer Science students. Inter-disciplinary subjects such as IoT, Bioinformatics provides a huge contribution in research for computer science students.
  4. Apart from interdisciplinary research, mainstream research in computer science also provides a huge scope for the student both nationally and internationally.

 As a computer science engineer, there are plenty of opportunities in Government sectors as well as private sectors. A focused, sincere and conceptual student has all the possibilities to touch the sky.